Skip to main content
Premium Trial:

Request an Annual Quote

Type 2 Diabetes Mechanisms, Risk Genes Identified in GWAS Meta-Analysis

NEW YORK – By focusing on genetic loci linked to the insulin precursor protein proinsulin, an international team led by investigators in the US and the UK has tracked down candidate risk genes for type 2 diabetes (T2D) and related mechanisms of T2D development.

"This study quadrupled the sample size of the largest previous meta-analysis and doubled the number of proinsulin association signals, implicating candidate genes that regulate insulin processing and glucose regulation," co-senior and co-corresponding author Karen Mohlke, a genetics researcher at the University of North Carolina at Chapel Hill, and her colleagues wrote.

As they reported in the American Journal of Human Genetics on Monday, members of the "Meta-Analysis of Glycemic and Insulin Traits Consortium" first tracked down three dozen variants with ties to fasting proinsulin levels with a genome-wide association study meta-analysis that included nearly 45,900 individuals from 16 prior studies. These involved participants with European ancestry who were profiled by genotyping and trait testing but did not include anyone with a T2D diagnosis or related blood traits.

"Insulin secretion is critical for glucose homeostasis, and increased levels of the precursor proinsulin relative to insulin indicate pancreatic islet beta-cell stress and insufficient insulin secretory capacity in the setting of insulin resistance," the authors reasoned, explaining that results from their new meta-analysis and follow-up analyses "show how detailed genetic studies of an intermediate phenotype can elucidate mechanisms predisposing to disease."

The fasting proinsulin set spanned 36 signals at 30 risk loci, including 28 primary associations and six more signals stemming from conditional analyses found after adjusting for body mass index. The collection encompassed 12 loci linked to proinsulin levels in the past, along with 10 glycemic trait-associated loci, the team reported, consistent with past studies linking the insulin precursor to both T2D and related hyperglycemia traits.

The investigators delved further into the proinsulin-associated loci using data on individuals' blood glucose levels and other glycemic traits, expression quantitative trait locus profiles gleaned from RNA sequences representing human islet and subcutaneous adipose tissues from more than 400 individuals apiece, ATAC-seq analyses, and follow-up cell line experiments.

While roughly half of the proinsulin-associated variants corresponded with higher blood glucose level, other variants were linked to low proinsulin levels in combination with elevated blood glucose levels.

With eQTL and other data, meanwhile, the team tracked down several islet beta cell- and glycemic trait-related genes, including candidate diabetes risk genes such as MADD, RNF6, CDK8, ARSG, WIPI1, and SLC7A14 with enhanced or lower-than-usual expression in individuals with elevated proinsulin expression. The risk loci also encompassed genes implicated in processes ranging from prohormone convertase enzyme activity, lysosomal activity/autophagy, or vesicle trafficking to beta-cell function or transcriptional regulation.

After using conditional analyses to focus in on five genes near GWAS loci, including the MADD gene, the researchers delved into regulatory features found at the MADD locus with transcriptional reporter assays in mouse and rat insulinoma cell lines.

"Integration of proinsulin loci with complementary glycemic traits, expression data in trait-relevant tissues, and functional follow-up provide candidate genes for T2D and hypotheses on potential avenues of mechanism for known T2D loci," the authors explained.

"While these proinsulin meta-analyses include a larger sample size, the difficulty and cost in obtaining proinsulin measurements limits the sample size compared to studies of many other glycemic traits," they added, arguing that similar studies in the future "will benefit from more and more diverse cohorts."